Method and apparatus for automated shopper checkout using radio frequency identification technology

ABSTRACT

A method and apparatus involve: providing a plurality of products that are each associated with a respective radio frequency identification tag; using radio frequency identification technology to automatically identify specific products in a group of products collected by a shopper; and evaluating whether or not to obtain payment from the shopper based on the radio frequency identification of products in the group. Based on the result of the evaluation, either payment is obtained from the shopper on the basis of the radio frequency identification of products in the group, or else the products in the group are audited, and then payment is obtained on the basis of the products identified by the audit.

This application is a continuation of U.S. application Ser. No.12/267,068 filed Nov. 7, 2008, which claims the priority under 35 U.S.C.§ 119 of provisional application No. 60/996,262 filed Nov. 8, 2007, thedisclosure of both of which are hereby incorporated herein by reference.

FIELD OF THE INVENTION

This invention relates in general to techniques for shopper checkoutand, more particularly, to techniques that facilitate efficient checkoutof a shopper.

BACKGROUND

Shopper checkout is the process of identifying all of the productsselected by a shopper, and then obtaining payment from the shopper forthose products. Retail stores typically use two different techniques forshopper checkout. First, in the most common approach, a clerk employedby the store manually passes each product selected by the shopper past auniversal product code (UPC) scanner, and the scanner reads the UPC codeon each product. The UPC scanner is coupled to a computer, and thecomputer uses the scanned UPC code from each product to retrieve from astored product list an identification of the product, and also the priceof the product. The computer sums the individual prices of all productsscanned in order to obtain a subtotal, and then adds any applicabletaxes or other charges to the subtotal, thereby obtaining the totalamount owed by the shopper. The clerk then obtains payment of that totalamount from the shopper in order to complete the checkout process.

The other common approach is self-service checkout. During self-servicecheckout, it is the shopper rather than a store clerk who manually scansthe UPC code on each product. A single clerk is typically present tomonitor four or more self-service checkout stations, and to deal withany questions or problems encountered by shoppers operating theself-service checkout stations. The self-service approach issignificantly less expensive for the store, because the store pays wagesand benefits only for the single clerk who monitors several self-servicecheckout stations, instead of paying wages and benefits for severalclerks who are each located at a respective different checkout station.On the other hand, the self-service approach has some drawbacks. Forexample, a shopper may inadvertently or intentionally fail to scan theUPC code on one or more products, such that the computer calculating thetotal amount due is not aware of those products and thus omits theirprices from the total. As a result, the shopper ends up taking home oneor more products that the shopper did not pay for.

While these traditional approaches have each been generally adequate fortheir intended purposes, they each have some drawbacks, and neither hasbeen entirely satisfactory in all respects.

BRIEF DESCRIPTION OF THE DRAWINGS

A better understanding of the present invention will be realized fromthe detailed description that follows, taken in conjunction with theaccompanying drawings, in which:

FIG. 1 is a diagrammatic fragmentary sectional top view of a portion ofa retail store, and in particular shows a portion of the store whereshoppers check out and pay for their purchases.

FIG. 2 is a diagrammatic fragmentary side view showing in an enlargedscale an interrogation zone present in the portion of the store depictedin FIG. 1, and also showing a shopper and a shopping cart that are inthe interrogation zone.

FIG. 3 is a block diagram of a control system that includes severalelectronic components shown in FIGS. 1 and 2, as well as a centralcomputer system that is operatively coupled to each of these electroniccomponents.

FIG. 4 is a diagrammatic view of a master product list that is stored ina memory of the computer system of FIG. 3.

FIGS. 5A and 5B are a flowchart showing a procedure that is part of theprocessing carried out by the computer system of FIG. 3.

FIGS. 6 and 7 show respective tables of information that are each storedin the memory of the computer system of FIG. 3, and that are used by theprocedure of FIGS. 5A and 5B.

FIG. 8 is a flowchart showing a procedure that is an alternativeembodiment of the procedure shown in FIGS. 5A and 5B.

FIGS. 9 and 10 show respective tables of information that can besubstituted for the table of FIG. 6, and used by the procedure of FIG.8.

DETAILED DESCRIPTION

FIG. 1 is a diagrammatic fragmentary sectional top view of a portion 10of a retail store, and in particular shows the portion of the storewhere shopper checkout occurs. Shopper checkout is the process ofidentifying all of the products selected by a shopper, and thenobtaining payment from the shopper for those products.

The portion 10 of the store includes a corridor or passage 12 thatsplits into two corridors or passages 13 and 14, each of which leads toa respective one of two checkout areas 17 and 18 that are partiallyseparated by a wall 21. The corridors 13 and 14 each open into theassociated checkout area 17 or 18 on one side thereof, and a single exitdoor 22 is provided on the opposite side thereof to permit shoppers toexit the store after completing the checkout process.

The checkout area 17 has three checkout stations 31, 32 and 33, and thecheckout area 18 has three checkout stations 34, 35 and 36. Each of thecheckout stations 31-36 includes a respective point-of-sale (POS)terminal 41-46 that is an electronic cash register of a known type. InFIG. 1, the checkout stations 31-36 are each manned by a respectiveperson 51-56 who is a store clerk. In an alternative configuration, thethree POS terminals 41-43 in the checkout area 17 could be replaced withself-service POS terminals of a type well known in the art. In the caseof self-service POS terminals, a single store clerk might be stationednearby to monitor all three checkout stations 41-43, or the store mightelect to provide no store clerk in the checkout area 17.

Shoppers who are waiting to check out proceed in single file down thecorridor 12. For example, FIG. 1 shows three shoppers 61-63 in thecorridor 12, each with a respective shopping cart 64, 65 or 66. Aninterrogation zone 68 is provided at the end of corridor 12 nearest thecorridors 13 and 14. The interrogation zone is discussed in more detaillater. In FIG. 1 the shopper 63 with the cart 66 is currently located inthe interrogation zone 68.

In FIG. 1, an electronic display 69 is provided at the intersection ofthe corridors 13 and 14. Depending on what happens in the interrogationzone 68, the display 69 will illuminate either an arrow pointing to theleft or an arrow pointing to the right, in order to indicate to theshopper in the interrogation zone that he or she should proceed downeither the corridor 13 or the corridor 14. FIG. 1 shows two shoppers 71and 72 with respective carts 73 and 74 who were directed to proceed downthe corridor 13 to the checkout area 17, and who are currently in theprocess of checking out. FIG. 1 also shows a shopper 77 with a cart 78who was directed to proceed down the corridor 14 to the checkout area18, and who is currently in the process of checking out.

FIG. 2 is a diagrammatic fragmentary side view showing in an enlargedscale the interrogation zone 68 of FIG. 1, and also showing the shopper63 and shopping cart 66 in the interrogation zone. The shopping cart 66contains several products 101-104 that the shopper 63 selected andintends to purchase. Although FIG. 2 shows four products 101-104, thecart 66 could alternatively include a larger or smaller number ofproducts. Each of the products 101-104 has a respective radio frequencyidentification (RFID) tag 106-109 mounted thereon. The tags 106-109 areeach a type of device well known in the art, and are therefore notillustrated and described here in detail. A child 113 is sitting in theshopping cart. The shopper 63 may also have one or more personal effectsin the cart, such as a purse.

In FIG. 2, the shopping cart 66 is resting on a scale 116 of a knowntype, which weighs the cart 66 and everything in the cart, and thenoutputs an electrical signal representing the total measured weight. Adigital camera 118 of a known type is stationarily supported above thescale 116. Although FIG. 2 shows only one camera 118, it wouldalternatively be possible to have two or more cameras that view the cartand its contents from different angles. The camera 118 records one ormore images of the cart and its contents as the cart passes below thecamera. The camera 118 then outputs these images in the form ofelectrical signals. The images from the camera 118 are then processedwith image processing software in an effort to identify items present inthe shopping cart 66, including the number of products 101-104, anychild 113, and any personal effects such as a purse. The camera 118 inFIG. 2 is responsive to visual light, and the recorded images aredigital photographs. Alternatively, however, the camera 118 could beresponsive to radiation in a waveband other than visible light, such asinfrared radiation, or low-level x-ray radiation.

As the shopper 63 continues to push the cart 66 in a forward direction,the cart 66 will pass between two RFID readers 121 and 122. The readers121 and 122 are each a device of a well-known type, and are thereforenot illustrated and described here in detail. The reader 121 isstationarily supported above the cart's path of travel, and the reader122 is embedded in the floor below the cart's path of travel. AlthoughFIG. 2 shows two readers 121 and 122, it would alternatively be possibleto have a larger or smaller number of readers. Also, FIG. 2 shows thereaders 121 and 122 located respectively above and below the path oftravel of the cart, but it would alternatively be possible to providethe readers 121 and 122 in other locations. For example, the readers 121and 122 could be provided on opposite sides of the path of travel of theshopping cart 66.

The readers 121 and 122 in FIG. 2 emit RFID signals of a known type. Asthe shopping cart 66 passes between the readers 121 and 122, the signalsemitted by the readers will reach most or all of the tags 106-109. Eachtag that receives a signal from either reader will produce in reply anRFID signal containing an identification code. The signal emitted byeach tag will then be received by one or both of the readers 121 and122. The identification code in each received signal can be used toidentify the tag that emitted the signal, and thus identify theparticular product associated with that tag.

In theory, all of the tags will receive the interrogation signals fromthe readers, such that all of the tags will produce a signal in reply,and all of the signals from the tags will be received by the readers.But as a practical matter, some types of products make it more difficultto scan tags than other types of products. For example, if a productincludes a significant amount of metal, the metal can provide a degreeof electromagnetic shielding that interferes with attempts tocommunicate with the tag on that metal product, and/or with tags onother products located near the metal product. Similarly, if a productcontains a significant amount of water, that may make it more difficultto communicate with the tag on that product, and/or with tags on othernearby products. As a result, the readers 121 and 122 may not always beable to accurately identify each and every product present in theshopping cart 66. A further consideration is that the readers 121 and122 cannot identify items in the shopping cart that do not have RFIDtags, such as the child 113, or personal effects of the shopper, such asa purse.

FIG. 3 is a block diagram of a control system 151 that includes severalelectronic components discussed above in association with FIGS. 1 and 2,as well as a central computer system 152 that is operatively coupled toeach of these electronic components. More specifically, FIG. 3 shows thePOS terminals 41-46 and the display 69 of FIG. 1, each of which iselectrically coupled to the central computer system 152. In addition,FIG. 3 shows the scale 116, camera 118 and readers 121-122 of FIG. 2,each of which is electrically coupled to the central computer system152. FIG. 3 does not show everything in the control system 151 or in thecomputer system 152, but instead only shows selected portions thereofthat facilitate an understanding of the present invention.

FIG. 3 shows a master terminal 156 that is electrically coupled to thecentral computer system 152. The master terminal 156 and the centralcomputer system 152 are not visible in FIGS. 1 and 2, because they arelocated in the business office of the illustrated store, where they canbe accessed by store management but not shoppers. Store management canprovide the master terminal 156 with a password, and then use the masterterminal to adjust data within the central computer system 152. In thedisclosed embodiment, the central computer system 152 includes computerhardware in the form of a conventional, commercially-available computerof the type commonly known as a personal computer. For example, thehardware of the computer system 152 could be a standard personalcomputer obtained commercially from Dell, Inc. of Round Rock, Tex.Alternatively, however, the hardware of the computer system 152 could beany other suitable computer hardware.

The computer system 152 includes a processor 161 and a memory 162. Theprocessor 161 is a microprocessor of a known type, and is therefore notdescribed here in detail. The memory 162 is a diagrammaticrepresentation of the storage available within the central computersystem 152, and may include more one than one type of memory. Forexample, the memory 162 may include one or more of a read only memory(ROM), a random access memory (RAM), a flash memory, a hard disc drive,or any other suitable type of memory.

FIG. 3 diagrammatically shows some of the information that is maintainedwithin the memory 162. More specifically, the memory 162 stores asoftware program 166 that is executed by the processor 161. A portion ofthe program 166 is image processing software 167. As mentioned earlier,the image processing software 167 accepts digital images produced by thecamera 118, and analyzes these images in an effort to identify the cartand items disposed in the cart, such as the products 101-104 (FIG. 2),any child 113, and/or any personal effects such as a purse.

The memory 162 also stores several segments of cart data, three of whichare shown at 171, 172 and 173. Each segment of cart data 171-173 iscreated as a respective shopping cart passes through the interrogationzone 68, contains information derived from that cart in theinterrogation zone 68, and is maintained in the memory 162 untilcheckout of that particular cart has been completed. The segments ofcart data 171, 172 and 173 are all similar, and therefore only thesegment 171 is shown and described in detail.

More specifically, the segment of cart data 171 includes a measured cartweight 176, which is the total weight of the particular cart and itscontents, as measured by the scale 116 in the interrogation zone. Thecart data segment 171 also includes an RFID tag count 177, which is thenumber of RFID tags detected in that cart by the readers 121 and 122.The cart data 171 further includes an RFID product list 178. Asdiscussed above, the RFID tag on each product produces a wireless signalcontaining a code that is used to identify the particular product onwhich that tag is mounted. The RFID product list 178 is a list of allproducts identified in the cart through communication with RFID tags onthe products. The cart data segment 171 also includes an actual productcount 179, which is the number of separate products detected by theimage processing software 167, based on the images produced by thecamera 118.

The memory 162 stores a cart tare weight value 182, which is thepredetermined weight of the shopping cart 66 when it is empty.

As discussed above, some products make it more difficult to read RFIDtags than other products. Consequently, it is possible for the RFIDreaders 121 and 122 to miss one or more products in a cart. Similarly,the camera 118 produces images that are analyzed in an effort toidentify each of the products in the cart. However, the image processingsoftware 167 may not be able to accurately identify each and everyproduct in the cart. For example, a small product may be located beneathsome larger products in the cart, and thus may not be visible in any ofthe images from the camera 118. Consequently, for any given shoppingcart, product lists generated from information obtained in theinterrogation zone 68 using RFID technology or imaging technology may ormay not include all of the products actually present in the cart.

The store may elect to permit a shopper to check out based solely on aproduct list generated from information obtained in the interrogationzone 68. However, if that list is incomplete, the shopper would takehome one or more products that the shopper did not pay for. This iscommonly referred to as shrinkage of the store's inventory.

On any given day (or during certain periods of the day), a store may notbe very busy, and this or other circumstances may make the storeunwilling to accept much shrinkage. Accordingly, instead of checking outall carts based on product list(s) generated from information obtainedin the interrogation zone 68, the store may prefer to select a subset ofthe carts that are checking out, and perform a double-check or audit ofthe products actually present in each of those carts, in order togenerate a very accurate product list for each such cart that is thenused for checkout. On the other hand, on any given day (or duringcertain periods of the day), the store may be very busy and may have along line of shoppers waiting to check out, and this or othercircumstances may make the store more willing to accept a higher risk ofshrinkage, in order to keep shoppers happy by checking them out morerapidly. Accordingly, the store may subject fewer carts (or no carts) toa double-check or audit.

In FIG. 3, the memory 162 of the computer system 152 stores a businessvalue 183. The business value 183 can be set by store management usingthe master terminal 156, and specifies the store's current willingnessto tolerate shrinkage. More specifically, the business value 183 is aninteger number between 1 and 10, inclusive. The values of 1 to 10represent a sliding scale of tolerance for shrinkage, where 1 representsthe maximum tolerance for shrinkage with the smallest percentage ofcarts being double-checked or audited, and 10 represents the leasttolerance for shrinkage with a substantially higher percentage of cartsbeing double-checked or audited.

The business value 183 influences the determination of whether eachshopper in the corridor 12 (FIG. 1) will be directed to proceed down thecorridor 13 or down the corridor 14, in a manner discussed in moredetail later. Carts that are directed down the corridor 13 end up in thecheckout area 17, where checkout is completed using the RFID productlist 177 generated from information obtained using RFID technology inthe interrogation zone 68. In contrast, carts that are directed toproceed down the corridor 14 end up in the checkout area 18, where adouble-check or audit is carried out on each such cart, and thencheckout is completed based on the results of the double-check or audit.For example, in the checkout area 18, one of the clerks 54-56 may use astandard UPC scanner to manually scan the universal product code (UPC)on each product in a cart, in order to generate a highly accurateproduct list that is then used for checkout.

The memory 162 stores a set of weighting values 184. In the disclosedembodiment, there are six weighting values W1, W2, W3, W4, W5 and W6,each of which is an integer value between 1 and 5 inclusive, where 5represents the greatest weight, and 1 represents the least weight. Theweighting values 184 can each be adjusted by store management throughthe master terminal 156. The memory 162 also stores a default threshold186. In the disclosed embodiment, the default threshold is a singleinteger between 0 and 100 inclusive, and represents a percentage, suchas 65%. The default threshold 186 can be adjusted by store managementthrough the master terminal 156.

The memory 162 also stores a master product list 188. FIG. 4 is adiagrammatic view of the master product list 188. The master productlist 188 is shown in FIG. 4 as a table, with a separate row for eachtype of product carried by the store. Each row has the same set offields, and some of these fields are depicted in the first row in FIG.4. In particular, for each product or row, there is a field 191 settingforth the name of the product, a field 192 setting forth theindustry-standard UPC code for that product, a field 193 setting forththe price charged by the store for that product, a field 194 settingforth the weight of the product, and a field 195 setting forth adifficulty rating.

Each difficulty rating 195 is an integer number between 1 and 10,inclusive. As discussed above, some types of products (such as thosethat contain metal or water) are more likely to interfere with thescanning of RFID tags than other types of products. The numericaldifficulty rating in the field 195 is an indication of the extent towhich the associated product is likely to interfere with scanning of theRFID tag mounted on that product, or RFID tags on other nearby products.A value of 1 represents the least degree of interference or difficulty,and a value of 10 represents the greatest degree of interference ordifficulty. Store management can use the master terminal 156 to changethe information in the master product list 188, including the difficultyratings 195. For simplicity, FIG. 4 shows the difficulty ratings 195 asan integral portion of the master product list 188. However, thedifficulty ratings 195 could alternatively be maintained in a separatelist.

Referring again to FIG. 3, the memory 162 in the central computer system152 also stores several tables 197, each of which is discussed in moredetail later.

FIGS. 5A and 5B are a flowchart showing a procedure that is a portion ofthe processing carried out by the processor 161 under control of theprogram 166. The flowchart of FIGS. 5A and 5B shows how the processor161 decides whether to direct a shopper along either the corridor 13 orthe corridor 14. More specifically, as soon as a given shopping cart hasbeen interrogated in the interrogation zone 68 (FIGS. 1 and 2), theprocessor 161 carries out an evaluation that is based primarily on datacollected during the interrogation. Then, the processor makes a decisionabout whether to direct the cart along the corridor 13 to the checkoutarea 17, or along the corridor 14 to the checkout area 18. As discussedabove, in the checkout area 17 shoppers check out and pay based on theproduct list compiled using RFID technology. In contrast, in thecheckout area 18, the products in each cart are audited (for example byscanning UPC codes), in order to generate a new and accurate productlist that is then used for checkout.

As discussed in more detail below, the procedure of FIGS. 5A and 5Binvolves successive evaluation of six different criteria. Each criterialooks for a respective different condition that suggests a likelihoodthe RFID product list 178 might not be fully accurate. If the cart failsto meet any one of these six criteria, then the contents of the cart areaudited in the checkout area 18. On the other hand, if the cart meetsall six criteria, then the cart is sent to checkout area 17, and is notaudited.

In more detail, the routine of FIGS. 5A and 5B is entered at block 211,and then control proceeds to block 212. In block 212, the processor 161prepares a filtered product list. In this regard, FIG. 6 shows a tablethat is one of the tables stored at 197 (FIG. 3) in the memory 162, andthat has six columns 216-221. The left column 216 sets forth eachpossible value of the business value stored at 183 in the memory 162(FIG. 3), and the adjacent column 217 shows a corresponding difficultythreshold. In the disclosed embodiment, the difficulty threshold happensto be the same as the business value. For example, if the business valueis currently 1 then the difficulty threshold is 1, and if the businessvalue is 5 then the difficulty threshold is 5. The processor usescolumns 216 and 217 to identify the difficulty threshold associated withthe current value of the business value 183.

The processor then identifies each product from the master product list188 that currently has a difficulty rating (195 in FIG. 4) exceeding thecurrent difficulty threshold obtained from column 217. These productscollectively constitute the filtered product list. The processor thencompares this filtered product list to the RFID product list 178 (FIG.3) for the shopping cart that has just been interrogated. Basically, theprocessor is looking for products (if any) that are on both lists. Anyproduct present on both lists will have a difficulty rating thatsuggests the product might have blocked access to one or more RFID tags,such that one or more products actually present within the cart may notappear on the RFID product list. In FIG. 5A, control proceeds to block226, where the processor checks to see whether the comparison yieldedany matches, or in other words whether any product was on both lists. Ifany product is on both lists, then the RFID product list may not beaccurate, and control proceeds to block 227.

In block 227, the processor causes the display 69 in FIG. 1 toilluminate an arrow pointing to the right, indicating to the shopper inthe interrogation zone 68 that he or she should proceed down thecorridor 14 to the checkout area 18. In the checkout area 18, theproducts in the cart will be carefully audited (for example by having astore clerk manually scan the UPC code on each product). Checkout willthen be completed using the product list from the audit. From block 227,the processor proceeds to block 228, and exits the routine of FIG. 5B.

Referring back to block 226, if it was determined that that there was nomatch, or in other words that no product on the RFID product list wasalso on the filtered product list, then control proceeds to block 231.In block 231, the processor 161 takes the RFID tag count 177 (FIG. 3),and compares it to a tag count threshold. More specifically, withreference to FIG. 6, the processor locates the current business value incolumn 216, and then selects a corresponding tag count threshold fromcolumn 218. In essence, as the number of products in the shopping cartincreases (such that the number of RFID tags also increases), it becomesmore difficult to accurately identify each and every tag with RFIDtechnology. Stated differently, as the number of products and tagsincreases, there is a progressively increasing chance that the RFIDidentification process may have missed one or more of the products in acart. In block 231, the processor compares the RFID tag count 177 to thetag count threshold obtained from column 218. If the tag count exceedsthe threshold, then control proceeds to block 227 for an audit of theproducts in the cart. It will be noted from FIG. 6, that, as thebusiness value progressively increases, representing a progressivelyincreasing preference for accuracy at checkout, the tag count thresholdin column 218 progressively decreases, meaning that progressivelysmaller product counts will trigger an audit.

In block 231, if the RFID tag count does not exceed the tag countthreshold, then control proceeds to block 232. In block 232, theprocessor takes the measured cart weight 176 (FIG. 3), and subtracts thecart tare weight 182 in order to determine the measured product weight,or in other words the total weight of all contents of the cart. Notethat this measured product weight will include not only products in thecart, but also anything else in the cart, such as a child 113 (FIG. 2)or personal effects such as a purse. However, to the extent that theimage processing software 167 can identify a child and/or personaleffects in the cart, it would optionally be possible to subtract apredetermined weight value from the measured product weight calculatedin block 232, in order to at least partially compensate for the childand/or the personal effect.

From block 232, control proceeds to block 233, where the measuredproduct weight calculated in block 232 is compared to a weightthreshold. With reference to FIG. 6, the processor locates the currentvalue of the business value in column 216, and then selects acorresponding weight threshold from column 219. If the measured productweight exceeds this weight threshold, then control proceeds from block233 to block 227 for an audit of the contents of the cart. In essence,as the weight of products in the cart increases, either the total numberof products is increasing, and/or the shopper is purchasing one or moreheavier and potentially more valuable products, such as a television. Itwill be noted from FIG. 6 that, as the value of the business value incolumn 16 progressively increases, representing a progressively greaterdesire for an accurate product list at checkout, the weight threshold incolumn 219 progressively decreases, meaning that progressively fewerand/or lighter products will trigger an audit.

If it is determined in block 233 that the measured product weight doesnot exceed the weight threshold, then control proceeds from block 233 toblock 236. In block 236, the processor takes the measured product weightdetermined in block 232, and checks to see whether this measured productweight and the RFID tag count 177 both fall within a specified windowwidth. In this regard, with reference to FIG. 6, the processor locatesthe current value of the business value in column 216, and then selectsa corresponding window width from column 220. FIG. 7 shows a table thatis one of the tables stored at 197 (FIG. 3) in the memory 162, and thathas 10 columns or “buckets” each relating a respective range of RFID tagcounts to a respective weight range. The window width obtained fromcolumn 220 in FIG. 6 represents a number of adjacent columns in thetable of FIG. 7. For example, if the window width is 1, then thatrepresents one column in the table of FIG. 7, and the tag count and themeasured weight should both be within the same column. Reference numeral241 represents a window width of 1 column in FIG. 7. If the RFID tagcount is in the range of 21 to 25, then the measured product weightshould be in the range of 81 to 100 pounds. The window 241 is a slidingwindow, and could be associated with any single column in the table ofFIG. 7, but the tag count and weight both need to be in that samecolumn.

Alternatively, assume that the window width is 2 columns. Referencenumerals 242 and 243 show two different possible positions of a slidingwindow having a width of two columns. Taking both of the windowpositions 242 and 243 into account, it will be noted that if the RFIDtag count is in the range of 21 to 25, then the measured weight needs tobe somewhere within the three columns spanned by the two windowpositions 242 and 243, or in other words in the range of 61 to 120pounds. As still another example, reference numerals 244, 245 and 246show three different positions of a sliding window having a width of 3columns. Taking all three window positions 244, 245 and 246 intoaccount, it will be noted that if the RFID tag count is in the range of21 to 25, then the measured weight would need to be in the range of 41to 140 pounds.

These are examples of how the processor 161 determines in block 236(FIG. 5A) whether the measured product weight and the RFID tag count areboth within the current window width. If they are not both within thewindow width, then control proceeds to block 227 for an audit of thecontents of the cart. In essence, most shopping carts will exhibit arelatively close correlation between the number of tags read and themeasured weight of the products. But if there is a differential thatexceeds a specified tolerance (the current window width), then it raisesa question as to whether the RFID product was accurate, and thus anaudit is appropriate.

If it is determined in block 236 that the measured product weight andthe RFID tag count are both within the appropriate window width, thencontrol proceeds to block 251. In block 251, the processor takes theRFID product list 178, and looks up each listed product in the masterproduct list 188, in order to determine the actual weight 194 (FIG. 4)of that particular product. The processor then adds up all of theseweights in order to calculate the total weight of the products in thecart (as based on the information obtained using RFID technology). Then,the processor subtracts from the calculated product weight determined inblock 251 the measured product weight determined in block 232 (which isbased on the measurement made with scale 116). The processor takes theabsolute value of the difference, in order to obtain a weightdifferential that is a positive number.

The measured product weight and the calculated product weight shouldusually be approximately the same. In other words, the calculated weightdifferential should usually be relatively small. The larger the weightdifferential, the greater the likelihood that the RFID product list maynot include all of the products actually present in the cart, and thusthe greater the justification for auditing the products in the cart.Accordingly, in block 252, the weight differential calculated in block251 is compared to a differential threshold. In this regard, withreference to FIG. 6, the processor locates the current value of thebusiness value 183 in column 216, and then selects a correspondingdifferential threshold from column 221. It will noted that, as thebusiness value progressively increases, representing a progressivelygreater desire for accuracy in the product list used for checkout, thedifferential threshold in column 221 progressively decreases, such thatprogressively smaller weight differentials will trigger an audit of thecontents of the cart. In block 252, if the calculated weightdifferential exceeds the differential threshold obtained from column221, control proceeds to block 227 for an audit of the contents of thecart.

If it is determined in block 252 that the calculated weight differentialdoes not exceed the specified differential threshold, then controlproceeds to block 253. In block 253, the actual product count obtainedby analyzing images from the cameral 118 is compared to the RFID productcount obtained by interrogating RFID tags on products in the cart (or inother words the total number of products in the RFID product list 178 inFIG. 3). If these two product counts do not match exactly, then itsuggests the RFID product list might not be entirely accurate, and socontrol proceeds to block 227 in order to carry out an audit of thecontents of the cart. Otherwise, control proceeds from block 253 toblock 254.

In block 254, the processor causes the display 69 in FIG. 1 toilluminate an arrow pointing to the left, indicating that the shopper inthe interrogation zone 68 should proceed down the corridor 13 to thecheckout area 17, where checkout and payment will be carried out usingthe RFID product list 178. Control then proceeds to block 228, for anexit from the routine of FIG. 5B.

FIG. 8 is a flowchart showing a procedure that is an alternativeembodiment of the procedure shown in FIGS. 5A and 5B. In FIGS. 5A and5B, the procedure is influenced by the current state of the businessvalue 183 (FIG. 3), as explained in more detail above. In contrast, FIG.8 takes a different approach that does not involve use of the businessvalue 183. In particular, as discussed in more detail below, theprocedure of FIG. 8 successively evaluates six different criteria thatare similar to the six criteria used in the procedure of FIGS. 5A and5B. The check of each criteria results in the determination of arespective confidence level for that criteria, where the confidencelevel is expressed as a percentage. The six confidence levels are thenweighted, and combined to arrive at an overall confidence level. If theoverall confidence level is above a threshold, then the cart is directedto checkout area 17, where checkout is carried out using the RFIDproduct list 178. On the other hand, if the overall confidence level isbelow the threshold, then the cart is directed to checkout area 18,where an audit is performed, and checkout is carried out using theproduct list from the audit.

Turning now in more detail to FIG. 8, processing begins at 301, andproceeds to block 302. In block 302, the processor 161 takes the RFIDproduct list 178 (FIG. 3), and looks each listed product up in themaster product list 188 (FIGS. 3 and 4), in order to obtain the currentdifficulty rating 195 for that product. The processor then adds up allthese difficulty ratings, and divides the sum by the number of productsin the RFID product list, in order to obtain an average of thedifficulty ratings for all products in the RFID product list 178. Theaverage will necessarily be a number between 1 and 10. The processormultiplies this average by 10, in order obtain a percentage, and thensubtracts this percentage from 100% in order to obtain a firstpercentage “%1”.

Control then proceeds from block 302 to block 303. In block 303, theprocessor uses the RFID tag count 177 to determine a second percentage“%2”. More specifically, FIG. 9 is a table that is one of the tablesstored at 197 (FIG. 3) in the memory 162, and that has four columns 306,307, 308 and 309. The left column 306 lists different possible valuesfor the RFID tag count, and the right column 309 gives correspondingconfidence levels, each expressed as a respective different percentage.The processor looks the RFID tag count 177 up in the left column 306,and then selects the associated percentage from column 309, for use asthe second percentage “%2”.

The processor then proceeds from block 303 to block 311. In block 311,the processor calculates a measured product weight in the same manneralready discussed above in association with block 232 in FIG. 5A. Theprocessor looks this measured product weight up in column 307 of thetable in FIG. 9, and then selects the corresponding percentage from theright column 309 for use as a third percentage “%3”.

The processor then proceeds from block 311 to block 312. In block 312,the processor determines a forth percentage “%4” based on the RFID tagcount 177 (FIG. 3), and the measured product weight calculated in block311. More specifically, with reference to FIG. 7, the processoridentifies the column in FIG. 7 that corresponds to the RFID tag count177, and also identifies the column that contains the measured productweight. If they are both in the same column, then the number of columnsspanned is 1. If they are not in the same column but are in adjacentcolumns, then the number of columns spanned is 2. Similarly, if they arein different columns that have a single further column between them,then the number of column spanned is three. In this manner, theprocessor thus determines the number of columns in FIG. 3 that arespanned by the RFID tag count and the measured product weight.

FIG. 10 is a table that is one of the tables stored at 197 (FIG. 3) inthe memory 162. The left column 316 contains possible values for thenumber of columns spanned in FIG. 7, and the right column 317 containsrespective confidence levels, each expressed as a percentage. Afterdetermining the number of columns spanned in FIG. 7, the processor looksthis number up in the left column 316 of the table in FIG. 10, and thenselects the corresponding percentage from column 317 to serve as thefourth percentage “%4”.

The processor then proceeds from block 312 to block 321. In block 321,the processor uses the RFID product list 178 and the master product list188 (FIG. 3) to calculate a weight differential, in the same mannerdiscussed above in association with block 251 of FIG. 5B. The processorlooks this weight differential up in column 308 of the table in FIG. 9,and then selects the corresponding percentage from column 309 for use asa fifth percentage “%5”.

The processor then proceeds to block 322, where it compares the actualproduct count 179 (FIG. 3) to the RFID product count, which is thenumber of products present in the RFID product list 178. This isequivalent to the comparison that was already discussed above inassociation with block 253 of FIG. 5B. If the actual product count isexactly the same as the RFID product count, then the processor proceedsto block 323, where it sets a sixth percentage “%6” to be 100%.Alternatively, if the actual product count and RFID product count arefound to be different in block 322, then the processor proceeds to block324, where it sets the sixth percentage “%6” to be 0%. From either ofblocks 323 or 324, the processor proceeds to block 326.

As discussed above in association with FIG. 3, the memory 162 containsweighting values 184, and in particular six weighting values W1, W2, W3,W4, W5 and W6 that are each an integer between 1 and 5, inclusive. Asshown in block 326, the processor calculates for the cart of interest anoverall confidence level “% C”, in particular by multiplying each of thepercentages %1, %2, %3, %4, %5 and %6 by a respective weighting valueW1, W2, W3, W4, W5 or W6, by then summing the products of thesemultiplications, and by then dividing the sum of the products by the sumof the weighting values.

The processor then proceeds to block 327, where it compares thecalculated overall confidence level % C to the default threshold 186(FIG. 3). As discussed earlier, the default threshold 186 is apercentage specified by store management, such as 65%. If the calculatedconfidence level % C is greater than the default threshold, then theprocessor proceeds from block 327 to block 238, where the cart ofinterest is sent for an audit, and then checkout is performed using theproduct list from the audit. In other words, in FIG. 1, the display 69is used to direct the shopper in the interrogation zone 68 to proceeddown the corridor 14 to the checkout area 18. In contrast, if it isdetermined in block 327 that the overall confidence level % C does notexceed the default threshold, then the processor proceeds from block 327to block 239, where the cart of interest is sent to have checkoutcompleted using the RFID product list 178 (FIG. 3). More specifically,with reference to FIG. 1, the display 69 is used to direct the shopperin the interrogation zone 68 to proceed down the corridor 13 to thecheckout area 17. From either of blocks 328 and 329, the processorproceeds to block 332, for an exit from the routine of FIG. 8.

The embodiment that is shown in the drawings and described above isconfigured with a single interrogation zone 68, through which allshoppers must pass on their way to any of the checkout stations 31-36.Further, the checkout stations are organized into two groups, wherecheckout stations 31-33 in checkout area 17 are used for RFID checkout,and checkout stations 34-36 in checkout area 18 are used to audit carts.Alternatively, however, the central interrogation zone 68 could beeliminated, and a single group of checkout stations could be provided,where the checkout stations are all identical. A shopper could freely goto any of the checkout stations. Each checkout station would have itsown dedicated interrogation zone. Each checkout station would be capableof checking out a shopper based on either the RFID product list or acart audit, depending on the result of the interrogation performed inthat checkout station's dedicated interrogation zone.

The embodiment shown in the drawings is capable of accommodating thepresence in a shopping cart 66 of a child 133, or personal effects.Alternatively, however, in order to simplify the processing task carriedout by the image processing software 167, it would be possible torequire each shopper to remove any child and/or personal effects from ashopping cart before the cart enters the interrogation zone 68. Stillanother alternative would be to provide shopping carts that lack a childseat, in order to significantly reduce the likelihood that a child maybe sitting in the cart when the cart reaches the interrogation zone.

For simplicity in disclosing the embodiment that is shown in thedrawings, it has been assumed that all shopping carts in the store areidentical, and thus have the same tare weight. However, some stores havetwo or more different types of shopping carts, such as traditionalshopping carts and flatbed carts. Where there are two or more differenttypes of carts, each type of cart will typically have a respectivedifferent tare weight. In that type of situation, each shopping cartwould have an RFID tag mounted thereon. As a cart is passing through theinterrogation zone 68 and the tags on products in the cart are beinginterrogated using RFID technology, the tag on that shopping cart wouldalso be interrogated. Based on the information obtained from the cart'stag, the central computer system 152 would know the particular type ofcart that is currently in the interrogation zone 68, and thus theappropriate tare weight to use in carrying out calculations relating tothe weight of that cart.

Although a selected embodiment has been illustrated and described indetail, it should be understood that a variety of substitutions andalterations are possible without departing from the spirit and scope ofthe present invention, as defined by the claims that follow.

What is claimed is:
 1. A method, comprising: providing a plurality ofproducts that are each associated with a respective radio frequencyidentification tag; assigning a business value selected by a seller froma plurality of values, where each of the plurality of values representsa different threshold level of a current willingness of the seller totolerate shrinkage ranging between a willingness to tolerate a minimumlevel of shrinkage, one or more intermediate levels of shrinkage and amaximum level of shrinkage, automatically selecting, by a computersystem and based on the assigned business value, a value for each of aplurality of thresholds comprising a tag reading difficulty threshold, atag count threshold, a product weight threshold, a product weight andtag count range threshold, and a product weight differential threshold,wherein each of the plurality of thresholds comprises multipleselectable values, the assigned business value defining the value foreach threshold, wherein tag reading difficulty thresholds representdifferent levels of difficulty involved in identifying the product usingthe radio frequency identification technology; tag count thresholdsrepresent a different number of the products identified using the radiofrequency identification technology; product weight thresholds representa different weight of the products identified using the radio frequencyidentification technology; product weight and tag count range thresholdsrepresent different relationships between product weight and number oftags of the products identified using the radio frequency identificationtechnology; and product weight differential thresholds representdifferent product weight differentials between a measured product weightand a calculated product weight of the products identified using theradio frequency identification technology; using a scale coupled to thecomputer system and located proximate to a point of sale (POS) checkoutarea to output a signal corresponding to a total weight including atleast a container and a group of products collected by a shopper withinthe container as the shopper enters the POS checkout area; using one ormore cameras coupled to the computer system and located proximate to thePOS checkout area to output digital signaling corresponding to thecontainer and the group of products collected by the shopper as theshopper enters the POS checkout area; using radio frequencyidentification technology obtained from at least one RFID tag readercoupled to the computer system and located proximate to the POS checkoutarea in real time as the shopper enters the POS checkout area toautomatically identify specific products within the group of theproducts collected by the shopper; and determining, using the computersystem and data obtained from each of the using steps and according to aset of rules, a value for each of a plurality of properties relating tothe identified specific products collected by the shopper, wherein theplurality of properties comprises a tag reading difficulty, a tag count,a product weight, a product weight and tag count range, and a productweight differential; evaluating, using the computer system and accordingto the set of rules, whether to obtain payment from the shopper based onthe radio frequency identification of products in the group and as afunction of the business value assigned by the seller, and wherein theevaluating comprises applying, using the computer system and accordingto the set of rules, in real time the one or more of the plurality ofthresholds having been automatically selected based on the assignedbusiness value to one or more of the determined values of the pluralityof properties of the identified products collected by the shopper, andbased on the result of the evaluating, carrying out one of: obtainingpayment from the shopper based on the radio frequency identification ofproducts in the group; and auditing the products in the group, and thenobtaining payment from the shopper based on the products identified bythe auditing.
 2. A method according to claim 1, including maintainingthe business value in a memory of the computer system, wherein theassigned business value is selectively adjustable by the seller to adifferent one of the plurality of values.
 3. The method of claim 2further comprising: adjusting the assigned business value to a newbusiness value selected by the seller, a new business value being adifferent one of the plurality of values.
 4. The method of claim 3wherein the adjusting the assigned business value can occur multipletimes during a period of business operation hours.
 5. A method accordingto claim 1, wherein the evaluating includes comparing the determinedvalue of the tag count for the products identified with radio frequencyidentification technology to the number of products identified with thedigital signaling from the one or more cameras; and carrying out theauditing and the obtaining of payment based on the auditing if thecomparison indicates that the determined value of the tag count for theproducts identified with radio frequency identification technology isdifferent from the number of products identified with the digitalsignaling from the one or more cameras.
 6. The method of claim 1,wherein the business value has a numeric value selected by the seller,wherein an increasing numeric value of the business value corresponds toan increasing preference of the seller for accuracy at checkout.
 7. Themethod of claim 1, further comprising a first point-of-sale terminal atthe POS checkout area, wherein the auditing the products comprisesauditing the products in the group at the first point-of-sale terminalby removing the products collected by the shopper from a productcontainer and individually scanning the removed products to identify thespecific products within the group of the products collected by theshopper, and then obtaining payment from the shopper at the firstpoint-of-sale terminal based on the products identified by the auditing;and wherein the obtaining the payment comprises obtaining payment fromthe shopper based on the radio frequency identification of products inthe group not at the first point-of-sale terminal.
 8. The method ofclaim 1, wherein the determining the value comprises determining, atleast in part using the signal, determined values for one or more of theproduct weight, the product weight and tag count range, and the productweight differential.
 9. The method of claim 1, wherein the evaluatingcomprises determining whether the value of the tag reading difficultyproperty for any of the specific products identified using the radiofrequency identification technology exceeds the selected value of thetag reading difficulty threshold.
 10. The method of claim 1, wherein theevaluating comprises determining whether the value of the tag countproperty for the specific products identified using the radio frequencyidentification technology exceeds the selected value of the tag countthreshold.
 11. The method of claim 1, wherein the determining the valuefor the product weight property is based on the signal from the scale,and wherein the evaluating comprises determining whether the value ofthe product weight property exceeds the selected value of the productweight threshold.
 12. The method of claim 1, wherein the determining thevalue for the product weight property is based on the signal from thescale, and wherein the evaluating comprises determining whether thevalue of the product weight property is within the selected value of theproduct weight and tag count range threshold of the value of the tagcount property for the specific products identified using the radiofrequency identification technology.
 13. The method of claim 1, furthercomprising: determining a calculated weight of the specific productsidentified using the radio frequency identification technology from adatabase of known product weights; and determining a value for a productweight differential based on the calculated weight and the value of theproduct weight property, and wherein the evaluating comprisesdetermining whether the value of the product weight differentialproperty exceeds the selected value of the product weight differentialthreshold.
 14. A method, comprising: providing a plurality of productsthat are each associated with a respective radio frequencyidentification tag; using a scale coupled to a computer system andlocated proximate to a point of sale (POS) checkout area to output asignal corresponding to a total weight including at least a containerand a group of products collected by a shopper within the container asthe shopper enters the POS checkout area; using one or more camerascoupled to the computer system and located proximate to the POS checkoutarea to output digital signaling corresponding to the container and thegroup of products collected by the shopper as the shopper enters the POScheckout area; using radio frequency identification technology obtainedfrom at least one RFID tag reader located proximate to the POS checkoutarea in real time as the shopper enters the POS checkout area toautomatically identify specific products within the group of theproducts collected by the shopper; and evaluating, using the computersystem and according to a set of rules, whether to obtain payment fromthe shopper based on the radio frequency identification of products inthe group and then, based on the result of the evaluating, carrying outone of: obtaining payment from the shopper based on the radio frequencyidentification of products in the group; and auditing the products inthe group, and then obtaining payment from the shopper based on theproducts identified by the auditing; wherein the evaluating according tothe set of rules includes: determining, using the computer system, thesignal from the scale, the digital signaling from the one or morecameras, and the specific products identified using the radio frequencyidentification technology, and according to the set of rules, a valuefor each of a plurality of properties relating to the identifiedspecific products collected by the shopper, wherein the plurality ofproperties comprises a tag reading difficulty, a tag count, a productweight, a product weight and tag count range, a product weightdifferential and a product count differential, determining, for each ofa plurality of different criteria that are each a function of the groupof products collected by the shopper and the determined values for eachof the plurality of properties, a confidence level having a value from aset of confidence levels corresponding to each criteria, resulting in aplurality of determined confidence levels specific to the productsidentified using radio frequency identification technology, wherein theplurality of different criteria comprises a tag reading difficultycriteria, a tag count criteria, a product weight criteria, a productweight and tag count range criteria, a product weight differentialcriteria, and a count differential criteria, wherein each of a pluralityof different criteria corresponds to a condition that suggests alikelihood that the radio frequency identification of products in thegroup may not be fully accurate, wherein the tag reading difficultycriteria corresponds to a level of difficulty involved in identifyingthe product using the radio frequency identification technology; the tagcount criteria corresponds to a number of the products identified usingthe radio frequency identification technology; the product weightcriteria corresponds to a weight of the products based on the signalfrom the scale; the product weight and tag count range criteriacorresponds to a relationship between the weight of the products basedon the signal from the scale and number of tags of the productsidentified using the radio frequency identification technology; theproduct weight differential criteria corresponds to a weightdifferential between a measured product weight using the signal from thescale and a calculated product weight of the products identified usingthe radio frequency identification technology; and the countdifferential criteria corresponds to a difference between the number ofitems identified using the radio frequency identification technology anda number of items identified using the one or more cameras, wherein eachof plurality of determined confidence levels comprise a tag readingdifficulty confidence level, a tag count confidence level, a productweight confidence level, a product weight and tag count range confidencelevel, a product weight differential confidence level, and a countdifferential confidence level; wherein the tag reading difficultyconfidence level is associated with a level of difficulty involved inidentifying the product using the radio frequency identificationtechnology; the tag count confidence level is associated with a numberof the products identified using the radio frequency identificationtechnology; the product weight confidence level is associated with aweight of the products based on the signal from the scale; the productweight and tag count range confidence level is associated with arelationship between the weight of the products based on the signal fromthe scale and number of tags of the products identified using the radiofrequency identification technology; the product weight differentialconfidence level is associated with a weight differential between ameasured product weight and a calculated product weight of the productsidentified using the radio frequency identification technology; and thecount differential confidence level is associated with a differencebetween the number of items identified using the radio frequencyidentification technology and a number of items identified using the oneor more cameras: determining an overall confidence value based on aweighting of the plurality of determined confidence levels; anddetermining the result of the evaluating as a function of the overallconfidence value relative to a default threshold defined by the sellerand selected by the seller from a plurality of default thresholds.
 15. Amethod according to claim 14, including using a further technologydifferent from radio frequency identification technology toautomatically identify the specific products within the group of theproducts collected by the shopper; and wherein the determining ofconfidence levels includes determining one of the confidence levels byassigning it a high level of confidence if the number of productsidentified with radio frequency identification technology equals thenumber of products identified with the further technology, and assigningit a low level of confidence if the number of products identified withradio frequency identification technology is different from the numberof products identified with the further technology.
 16. The method ofclaim 14, wherein the value of each of the plurality of confidencelevels comprises a percentage.
 17. The method of claim 14, wherein thedetermining the value comprises determining, at least in part using thesignal, determined values for one or more of the product weight, theproduct weight and tag count range, and the product weight differential.18. The method of claim 14 wherein the determining the overallconfidence value based on the weighting of the plurality of determinedconfidence levels comprises: multiplying each of the plurality ofdetermined confidence levels by a respective weighting factor to providea plurality of weighted determined confidence levels; summing each ofthe plurality of weighted determined confidence levels to provide asummed value; and dividing the summed value by a summed total of theplurality of determined confidence levels.
 19. A system, comprising: aninterrogation zone located proximate to a point of sale (POS) checkoutarea comprising: a weight measuring section comprising a scaleconfigured to output a signal corresponding to a total weight includingat least a container and a group of products collected by a shopperwithin the container as the shopper enters the POS checkout area; one ormore cameras configured to output digital signaling corresponding to thecontainer and the group of products collected by the shopper as theshopper enters the POS checkout area; a radio frequency identification(RFID) section that uses radio frequency identification technologycomprising at least one RFID tag reader configured to automaticallyidentify specific products within the group of products collected by theshopper in real time as a shopper enters the POS checkout area, whereineach of the identified specific products is associated with a respectiveradio frequency identification tag; and an evaluating section includinga computer system coupled to the scale, the one or more cameras and theRFID tag reader and is configured to obtain a business value assigned bya seller from a plurality of values, where each of the plurality ofvalues represents a different threshold level of a current willingnessof the seller to tolerate shrinkage ranging between a willingness totolerate a minimum level of shrinkage, one or more intermediate levelsof shrinkage and a maximum level of shrinkage, wherein the computersystem is configured to automatically select, based on the assignedbusiness value, a value for each of a plurality of thresholds comprisinga tag reading difficulty threshold, a tag count threshold, a productweight threshold, a product weight and tag count range threshold, and aproduct weight differential threshold, wherein each of the plurality ofthresholds comprises multiple selectable values, the assigned businessvalue defining the value for each threshold, wherein tag readingdifficulty thresholds represent different levels of difficulty involvedin identifying the product using the radio frequency identificationtechnology; tag count thresholds represent a different number of theproducts identified using the radio frequency identification technology;product weight thresholds represent a different weight of the productsidentified using the radio frequency identification technology; productweight and tag count range thresholds represent different relationshipsbetween product weight and number of tags of the products identifiedusing the radio frequency identification technology; and product weightdifferential thresholds represent different product weight differentialsbetween a measured product weight and a calculated product weight of theproducts identified using the radio frequency identification technology;wherein the computer system is configured to determine, using the signalfrom the scale, the digital signaling from the one or more cameras, andthe specific products identified using the radio frequencyidentification technology, and according to a set of rules, a value foreach of a plurality of properties relating to the identified specificproducts collected by the shopper, wherein the plurality of propertiescomprises a tag reading difficulty, a tag count, a product weight, aproduct weight and tag count range, and a product weight differential;wherein the computer system is further configured to evaluate accordingto a set of rules whether to obtain payment from the shopper based onthe radio frequency identification of products in the group and as afunction of the business value assigned by the seller; and wherein thecomputer system is further configured to evaluate by applying, accordingto the set of rules, in real time the one or more of the plurality ofthresholds having been automatically selected based on the assignedbusiness value to one or more of the determined values of the pluralityof properties of the identified specific products collected by theshopper, and then, based on the result of the evaluation, the computersystem calls for one of: obtaining payment from the shopper based on theradio frequency identification of products in the group; and auditing ofthe products in the group, followed by obtaining payment from theshopper based on the products identified by the auditing.
 20. The systemaccording to claim 19, wherein the group of products collected by theshopper is in a shopping container; wherein the scale measures theweight of the container and the products therein; and wherein thecomputer system subtracts the tare weight of the container from themeasured weight of the container and products therein in order to obtainthe value for the product weight of the products.
 21. The systemaccording to claim 19, including first and second point-of-saleterminals that are each operatively coupled to the computer system thefirst point-of-sale terminal being used for the obtaining of paymentfrom the shopper based on the radio frequency identification of productsin the group, and the second point-of-sale terminal being used for theauditing of the products in the group, and the obtaining payment fromthe shopper based on the products identified by the auditing.
 22. Thesystem of claim 19, wherein the computer system is configured todetermine whether the value of the tag reading difficulty property forany of the specific products identified using the radio frequencyidentification technology exceeds the selected value of the tag readingdifficulty threshold.
 23. The system of claim 19, wherein the computersystem is configured to determine whether the value of the tag countproperty for the specific products identified using the radio frequencyidentification technology exceeds the selected value of the tag countthreshold.
 24. The system of claim 19, wherein the computer system isconfigured to determine whether the value of the product weight propertyexceeds the selected value of the product weight threshold.
 25. Thesystem of claim 19, wherein the computer system is configured todetermine whether the value of the product weight property is within theselected value of the product weight and tag count range threshold ofthe value of the tag count property for the specific products identifiedusing the radio frequency identification technology.
 26. The system ofclaim 19, the computer system is further configured to: determine acalculated weight of the specific products identified using the radiofrequency identification technology from a database of known productweights; and determine a value for a product weight differential basedon the calculated weight and the value of the product weight property,and determine whether the value of the product weight differentialproperty exceeds the selected value of the product weight differentialthreshold.
 27. The system of claim 19 wherein the computer system isconfigured to: maintain the assigned business value in a memory of thecomputer system, wherein the assigned business value is selectivelyadjustable by the seller to a different one of the plurality of values;obtain an adjusted business value assigned by the seller from theplurality of values; and adjust the assigned business value to a newbusiness value selected by the seller, a new business value being adifferent one of the plurality of values.
 28. The system of claim 27wherein the computer system is configured to obtain adjusted businessvalues multiple times during a period of business operation hours.